Commit Graph

1436 Commits

Author SHA1 Message Date
Dmitry Yurov
31b308f882
Merge pull request #25808 from DmitryYurov:bug-25806-checkerboard-marker-black-tile
Enable checkerboard detection with a central / corner marker on a black tile #25808

This pull request closes the issue #25806.

The issue doesn't require any documentation - it's quite intuitive that the detection result shouldn't depend on the color of the marker's tile.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-07-08 12:36:56 +03:00
Kumataro
0b5b40179c calib3d: doc: enable line breaks in formulas 2024-07-07 07:15:28 +09:00
Maxim Smolskiy
cc6f85e1ba
Merge pull request #25427 from MaximSmolskiy:make-finding-corner-neighbor-symmetrical-in-ChessBoardDetector-findQuadNeighbors
Make finding corner neighbor symmetrical in ChessBoardDetector::findQuadNeighbors #25427

### Pull Request Readiness Checklist

The basic idea of finding pair of corners neighbors is to find best candidate for first corner and check if first corner quite good candidate for its best candidate. And we test first corner for its best candidate less than best candidate for first corner.

Idea of changes is to make finding corner neighbor symmetrical - find best candidate for first corner, find best candidate for second corner and match them as pair iff they are both best candidates for each other.

Additional advantage - it simplifies code and removes some code duplication.

I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```

There are minor changes in results
```
cell_img_size = 100 (default)

before

                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                          _none_none_blur             1.000000                        360               360                           0.630345
                    _none_none_gaussNoise             0.833333                        300               360                           0.623405
                          _none_none_none             1.000000                        360               360                           0.631517
                    _none_none_strongBlur             1.000000                        360               360                           0.630316
                   _none_undistorted_blur             1.000000                        360               360                           0.671232
             _none_undistorted_gaussNoise             1.000000                        360               360                           0.672619
                   _none_undistorted_none             1.000000                        360               360                           0.673669
             _none_undistorted_strongBlur             1.000000                        360               360                           0.671257
                   _perspective_none_blur             1.000000                       1080              1080                           0.588694
             _perspective_none_gaussNoise             0.805556                        870              1080                           0.599312
                   _perspective_none_none             1.000000                       1080              1080                           0.591063
             _perspective_none_strongBlur             1.000000                       1080              1080                           0.588604
            _perspective_undistorted_blur             1.000000                       1080              1080                           0.622081
      _perspective_undistorted_gaussNoise             1.000000                       1080              1080                           0.625704
            _perspective_undistorted_none             1.000000                       1080              1080                           0.624191
      _perspective_undistorted_strongBlur             1.000000                       1080              1080                           0.621618
             _strongPerspective_none_blur             1.000000                        360               360                           0.482934
       _strongPerspective_none_gaussNoise             0.166667                         60               360                           0.391551
             _strongPerspective_none_none             1.000000                        360               360                           0.480290
       _strongPerspective_none_strongBlur             0.333333                        120               360                           0.469080
      _strongPerspective_undistorted_blur             1.000000                        360               360                           0.503458
_strongPerspective_undistorted_gaussNoise             0.250000                         90               360                           0.448713
      _strongPerspective_undistorted_none             1.000000                        360               360                           0.504412
_strongPerspective_undistorted_strongBlur             0.166667                         60               360                           0.473791
                                      all             0.904167                      13020             14400                           0.600512
Total detected time:  139.65614900000008 sec

after

                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                          _none_none_blur             1.000000                        360               360                           0.630345
                    _none_none_gaussNoise             0.750000                        270               360                           0.636279
                          _none_none_none             1.000000                        360               360                           0.631517
                    _none_none_strongBlur             1.000000                        360               360                           0.630316
                   _none_undistorted_blur             1.000000                        360               360                           0.671232
             _none_undistorted_gaussNoise             1.000000                        360               360                           0.672619
                   _none_undistorted_none             1.000000                        360               360                           0.673669
             _none_undistorted_strongBlur             1.000000                        360               360                           0.671257
                   _perspective_none_blur             1.000000                       1080              1080                           0.588694
             _perspective_none_gaussNoise             0.888889                        960              1080                           0.594106
                   _perspective_none_none             1.000000                       1080              1080                           0.591064
             _perspective_none_strongBlur             1.000000                       1080              1080                           0.588604
            _perspective_undistorted_blur             1.000000                       1080              1080                           0.622081
      _perspective_undistorted_gaussNoise             1.000000                       1080              1080                           0.625703
            _perspective_undistorted_none             1.000000                       1080              1080                           0.624191
      _perspective_undistorted_strongBlur             1.000000                       1080              1080                           0.621618
             _strongPerspective_none_blur             1.000000                        360               360                           0.482934
       _strongPerspective_none_gaussNoise             0.166667                         60               360                           0.391551
             _strongPerspective_none_none             1.000000                        360               360                           0.480290
       _strongPerspective_none_strongBlur             0.333333                        120               360                           0.469080
      _strongPerspective_undistorted_blur             1.000000                        360               360                           0.503458
_strongPerspective_undistorted_gaussNoise             0.333333                        120               360                           0.422259
      _strongPerspective_undistorted_none             1.000000                        360               360                           0.504412
_strongPerspective_undistorted_strongBlur             0.166667                         60               360                           0.473791
                                      all             0.910417                      13110             14400                           0.599746
Total detected time:  142.40333700000005 sec

----------------------------------------------------------------------------------------------------------------------------------------------

cell_img_size = 10

before

                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                          _none_none_blur             0.991667                        357               360                           4.905091
                    _none_none_gaussNoise             0.750000                        270               360                           5.215633
                          _none_none_none             1.000000                        360               360                           4.943304
                    _none_none_strongBlur             0.916667                        330               360                           3.806217
                   _none_undistorted_blur             0.994444                        358               360                           5.220915
             _none_undistorted_gaussNoise             0.997222                        359               360                           4.542443
                   _none_undistorted_none             0.997222                        359               360                           4.340208
             _none_undistorted_strongBlur             0.161111                         58               360                           5.024331
                   _perspective_none_blur             0.629630                        680              1080                           4.825401
             _perspective_none_gaussNoise             0.966667                       1044              1080                           3.895425
                   _perspective_none_none             0.971296                       1049              1080                           3.920378
             _perspective_none_strongBlur             0.000000                          0              1080                                NaN
            _perspective_undistorted_blur             0.583333                        630              1080                           4.594335
      _perspective_undistorted_gaussNoise             0.999074                       1079              1080                           3.553195
            _perspective_undistorted_none             0.750000                        810              1080                           3.604110
      _perspective_undistorted_strongBlur             0.000000                          0              1080                                NaN
             _strongPerspective_none_blur             0.000000                          0               360                                NaN
       _strongPerspective_none_gaussNoise             0.000000                          0               360                                NaN
             _strongPerspective_none_none             0.083333                         30               360                           2.382460
       _strongPerspective_none_strongBlur             0.000000                          0               360                                NaN
      _strongPerspective_undistorted_blur             0.000000                          0               360                                NaN
_strongPerspective_undistorted_gaussNoise             0.000000                          0               360                                NaN
      _strongPerspective_undistorted_none             0.000000                          0               360                                NaN
_strongPerspective_undistorted_strongBlur             0.000000                          0               360                                NaN
                                      all             0.539792                       7773             14400                           4.209964
Total detected time:  2.6968930000000015 sec

after

                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                          _none_none_blur             0.991667                        357               360                           4.905091
                    _none_none_gaussNoise             0.750000                        270               360                           5.215633
                          _none_none_none             1.000000                        360               360                           4.943304
                    _none_none_strongBlur             0.916667                        330               360                           3.806217
                   _none_undistorted_blur             0.994444                        358               360                           5.220915
             _none_undistorted_gaussNoise             0.997222                        359               360                           4.542443
                   _none_undistorted_none             0.997222                        359               360                           4.340208
             _none_undistorted_strongBlur             0.161111                         58               360                           5.024331
                   _perspective_none_blur             0.629630                        680              1080                           4.825401
             _perspective_none_gaussNoise             0.966667                       1044              1080                           3.895425
                   _perspective_none_none             0.999074                       1079              1080                           3.865684
             _perspective_none_strongBlur             0.000000                          0              1080                                NaN
            _perspective_undistorted_blur             0.583333                        630              1080                           4.594335
      _perspective_undistorted_gaussNoise             0.999074                       1079              1080                           3.553195
            _perspective_undistorted_none             0.750000                        810              1080                           3.604110
      _perspective_undistorted_strongBlur             0.000000                          0              1080                                NaN
             _strongPerspective_none_blur             0.000000                          0               360                                NaN
       _strongPerspective_none_gaussNoise             0.000000                          0               360                                NaN
             _strongPerspective_none_none             0.000000                          0               360                                NaN
       _strongPerspective_none_strongBlur             0.000000                          0               360                                NaN
      _strongPerspective_undistorted_blur             0.000000                          0               360                                NaN
_strongPerspective_undistorted_gaussNoise             0.000000                          0               360                                NaN
      _strongPerspective_undistorted_none             0.000000                          0               360                                NaN
_strongPerspective_undistorted_strongBlur             0.000000                          0               360                                NaN
                                      all             0.539792                       7773             14400                           4.208308
Total detected time:  2.7706419999999983 sec
```

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-06-10 09:42:56 +03:00
Vincent Rabaud
1db6a8a1f3
Merge pull request #25665 from vrabaud:jacobian
Fix Homography computation. #25665

The bug was introduced in https://github.com/opencv/opencv/pull/25308

I am sorry I do not have a proper test.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-05-31 20:51:58 +03:00
fengyuentau
ca035e6dae fix type for ilp64 api 2024-05-31 22:47:57 +08:00
John Stechschulte
7b31cc7314
Merge pull request #24897 from JStech:fix-handeye
Fix handeye #24897

Fixes to the hand-eye calibration methods, from #24871.

The Tsai method is sensitive to poses separated by small rotations, so I filter those out.

The Horaud and Daniilidis methods use quaternions (and dual quaternions), where $q$ and $-q$ represent the same transform.
However, these methods depend on the gripper motion and camera motion having the same sign for the real part.
The fix was simply to multiply the (dual) quaternions by -1 if their real part is negative.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] ~~The feature is well documented and sample code can be built with the project CMake~~ N/A
2024-05-25 11:28:13 +03:00
Vincent Rabaud
500207785a Disambiguate cv::format
Otherwise, this test does not compile with C++20, which includes
std::format.
2024-05-23 10:41:03 +02:00
Rostislav Vasilikhin
83e32c4d37
Merge pull request #25511 from savuor:rv/hal_projectpoints
HAL for projectPoints() added #25511

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-05-20 10:42:17 +03:00
Dmitry Kurtaev
b1e01970ef
Merge pull request #25308 from dkurt:not_normalized_findHomography
Not-normalized output from findHomography #25308

### Pull Request Readiness Checklist

resolves https://github.com/opencv/opencv/issues/25133
resolves https://github.com/opencv/opencv/issues/4834
resolves https://github.com/opencv/opencv/issues/22166
resolves https://github.com/opencv/opencv/issues/18592

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-29 14:35:14 +03:00
inkredibl
2225b257cf
Merge pull request #25488 from inkredibl:doc-fix-findEssentialMat
Fix documentation for findEssentialMat to reflect how it actually works. #25488

Documentation for findEssentialMat() incorrectly states that the method uses the same cameraMatrix for both lists of points even though there are two cameraMatrix and distCoeffs.

Checked the code and it does the right thing i.e. uses cameraMatrix1, distCoeffs1 for points1 and cameraMatrix2, distCoeffs2 for points2.

Updated the documentation for the method to clarify what it does. The code itself is not changed.
2024-04-25 11:05:16 +03:00
LuukvandenBent
ae85e516c0
Merge pull request #25423 from LuukvandenBent:CalibrateHandEyeDatatypeFix
Calibrate hand eye datatype fix #25423

Fix for issue https://github.com/opencv/opencv/issues/25421.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2024-04-22 11:12:29 +03:00
Alexander Smorkalov
c622ffd95f
Merge pull request #25365 from MaximSmolskiy:take-first-suitable-neighbor-in-ChessBoardDetector-findQuadNeighbors
Take first suitable neighbor in ChessBoardDetector::findQuadNeighbors
2024-04-15 14:37:41 +03:00
Maksim Shabunin
148b2ec3e0 calib3d: increased AP3P test threshold for RISC-V platform 2024-04-09 23:53:50 +03:00
MaximSmolskiy
6b45cccc37 Take first suitable neighbor in ChessBoardDetector::findQuadNeighbors 2024-04-07 20:20:35 +03:00
Alexander Smorkalov
99cacaaad6
Merge pull request #25195 from MaximSmolskiy:use-initial-quads-corners-in-ChessBoardDetector-findQuadNeighbors
Use initial quads corners in ChessBoardDetector::findQuadNeighbors
2024-04-02 13:13:01 +03:00
Alexander Smorkalov
fd576d9e8e Added PNG instance of image for fisheye::undistort test as JPG is decoded differently with different libjpeg versions. 2024-03-28 12:02:58 +03:00
Maxim Smolskiy
ff9aeaceb0
Merge pull request #25177 from MaximSmolskiy:speed-up-adaptive-image-binary-threshold-in-findChessboardCorners
Speed up adaptive threshold in findChessboardCorners #25177

### Pull Request Readiness Checklist

If `block_size` hasn't been changed between iterations for same `k`, then all `adaptiveThreshold` arguments will be same and we can reuse result from previous iteration.

I tested this PR with benchmark
```
python3 objdetect_benchmark.py --configuration=generate_run --board_x=7 --path=res_chessboard --synthetic_object=chessboard
```
PR speed up chessboards detection by `7.5/17%` without any changes in detected chessboards number:
```
cell_img_size = 100 (default)

before
                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                                      all             0.904167                      13020             14400                           0.600512
Total detected time:  107.27875600000003 sec

after
                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                                      all             0.904167                      13020             14400                           0.600512
Total detected time:  99.0223499999999 sec

----------------------------------------------------------------------------------------------------------------------------------------------

cell_img_size = 10

before
                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                                      all             0.539792                       7773             14400                           4.209964
Total detected time:  2.989205999999999 sec

after
                                 category  detected chessboard  total detected chessboard  total chessboard  average detected error chessboard
                                      all             0.539792                       7773             14400                           4.209964
Total detected time:  2.4802350000000013 sec
```


See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-03-27 15:34:54 +03:00
Maxim Smolskiy
e3ff6ce0cc
Merge pull request #25182 from MaximSmolskiy:increase-decomposeProjectionMatrix-precision-for-small-scales
Increase decomposeProjectionMatrix precision for small scales #25182 

### Pull Request Readiness Checklist

Fix #23733

It is checked before that `|s| > DBL_EPSILON` (if not, then `s` will be equal to `0`, but `c` will be equal to `1`, then `z` will be equal to `1` and there will be no any problems with small values), so `sqrt(c^2 + s^2) >= |s| > DBL_EPSILON` and thus small values are already taken into account before and there is no need to add `DBL_EPSILON` to `c^2 + s^2` (and I think adding `DBL_EPSILON^2` instead of `DBL_EPSILON` would be more correct).

I ran `Python` script from issue.

`NumPy` and `SciPy` results
```
*Numpy*
P (case 1): 
[[1. 0. 0. 0.]
 [0. 1. 0. 0.]
 [0. 0. 1. 0.]]
Numpy, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
Numpy scaled 1e-6, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
P (case 2): 
[[52. -7.  4. 12.]
 [-6. 49. 12.  8.]
 [ 4. 17.  1.  0.]]
Numpy, R.T @ R - I: 
[[-8.88178420e-16 -3.86302608e-16 -2.52050796e-17]
 [-3.86302608e-16 -5.55111512e-16  7.11675423e-18]
 [-2.52050796e-17  7.11675423e-18 -5.55111512e-16]]
Numpy scaled 1e-6, R.T @ R - I: 
[[ 2.22044605e-16 -2.00683644e-16 -1.90063998e-17]
 [-2.00683644e-16  0.00000000e+00  1.16926308e-17]
 [-1.90063998e-17  1.16926308e-17  2.22044605e-16]]

*Scipy*
P (case 1): 
[[1. 0. 0. 0.]
 [0. 1. 0. 0.]
 [0. 0. 1. 0.]]
Scipy, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
Scipy scaled 1e-6, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
P (case 2): 
[[52. -7.  4. 12.]
 [-6. 49. 12.  8.]
 [ 4. 17.  1.  0.]]
Scipy, R.T @ R - I: 
[[-1.11022302e-16 -8.74062812e-18 -1.26178867e-17]
 [-8.74062812e-18 -1.11022302e-16  2.07820373e-17]
 [-1.26178867e-17  2.07820373e-17 -1.11022302e-16]]
Scipy scaled 1e-6, R.T @ R - I: 
[[0.00000000e+00 4.04691435e-17 1.12452918e-16]
 [4.04691435e-17 4.44089210e-16 3.74164141e-16]
 [1.12452918e-16 3.74164141e-16 4.44089210e-16]]

*Numpy*
Numpy, P' - P:
 [[ 1.35525272e-20 -9.31736242e-21  8.47032947e-22  3.38813179e-21]
 [-3.38813179e-21  6.77626358e-21  1.69406589e-21  0.00000000e+00]
 [-1.69406589e-21  0.00000000e+00  0.00000000e+00  4.85524279e-22]]

*Scipy*
Scipy, P' - P:
 [[0.00000000e+00 8.47032947e-22 3.38813179e-21 3.38813179e-21]
 [3.38813179e-21 1.35525272e-20 1.52465931e-20 1.52465931e-20]
 [8.47032947e-22 3.38813179e-21 2.54109884e-21 3.39866995e-21]]
```

`OpenCV` results before
```
*OpenCV*
P (case 1): 
[[1. 0. 0. 0.]
 [0. 1. 0. 0.]
 [0. 0. 1. 0.]]
OpenCV, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
OpenCV scaled 1e-6, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
P (case 2): 
[[52. -7.  4. 12.]
 [-6. 49. 12.  8.]
 [ 4. 17.  1.  0.]]
OpenCV, R.T @ R - I: 
[[ 2.22044605e-16 -9.12253504e-17 -2.20527203e-19]
 [-9.12253504e-17  0.00000000e+00 -9.12405093e-18]
 [-2.20527203e-19 -9.12405093e-18  2.22044605e-16]]
OpenCV scaled 1e-6, R.T @ R - I: 
[[-1.28197013e-06  1.30450769e-07  7.67357467e-09]
 [ 1.30450769e-07 -1.52141637e-06 -9.92455574e-09]
 [ 7.67357467e-09 -9.92455574e-09 -1.35328272e-06]]

*OpenCV*
OpenCV, P' - P:
 [[-6.75449076e-11  1.73936564e-11 -4.94463312e-12 -1.61106020e-11]
 [ 1.41759913e-11 -7.54512016e-11 -1.67717374e-11 -9.74644390e-12]
 [-2.90254385e-12 -2.53521998e-11 -1.49130587e-12  4.00724440e-13]]
```

`OpenCV` results after
```
*OpenCV*
P (case 1): 
[[1. 0. 0. 0.]
 [0. 1. 0. 0.]
 [0. 0. 1. 0.]]
OpenCV, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
OpenCV scaled 1e-6, R.T @ R - I: 
[[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
P (case 2): 
[[52. -7.  4. 12.]
 [-6. 49. 12.  8.]
 [ 4. 17.  1.  0.]]
OpenCV, R.T @ R - I: 
[[ 2.22044605e-16 -9.12253504e-17 -2.20527203e-19]
 [-9.12253504e-17  0.00000000e+00 -9.12405093e-18]
 [-2.20527203e-19 -9.12405093e-18  2.22044605e-16]]
OpenCV scaled 1e-6, R.T @ R - I: 
[[ 0.00000000e+00  4.36198333e-17 -2.66855078e-17]
 [ 4.36198333e-17  2.22044605e-16  3.17216400e-17]
 [-2.66855078e-17  3.17216400e-17 -2.22044605e-16]]

*OpenCV*
OpenCV, P' - P:
 [[ 6.77626358e-21  0.00000000e+00 -8.47032947e-22  1.69406589e-21]
 [-1.69406589e-21  6.77626358e-21  0.00000000e+00  3.38813179e-21]
 [ 8.47032947e-22  3.38813179e-21  2.11758237e-22  1.45657284e-21]]
```

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-03-27 12:43:56 +03:00
Alexander Smorkalov
4dc461717f
Merge pull request #25258 from AleksandrPanov:fix_rotated_symmetric_grid
Fix detect rotated SYMMETRIC_GRID
2024-03-26 17:23:05 +03:00
Alex
eaa88e7bc7 fix detect rotated grid, added test 2024-03-25 14:07:03 +03:00
MaximSmolskiy
7fe1664bbf Use initial quads corners in ChessBoardDetector::findQuadNeighbors 2024-03-10 17:49:27 +03:00
Alexander Smorkalov
0e524ee95a
Merge pull request #25145 from MaximSmolskiy:improve-contours-approximations-in-ChessBoardDetector-generateQuads-2
Improve contours approximations in ChessBoardDetector::generateQuads
2024-03-06 14:03:50 +03:00
Kumataro
b34ec57682
Merge pull request #25141 from Kumataro:fix25140_4.x
calib3d: doc: remove C API link (For 4.x) #25141

Related to #25140 (for 4.x)

### Pull Request Readiness Checklist

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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
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      Patch to opencv_extra has the same branch name.
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2024-03-05 16:24:42 +03:00
Alexander Smorkalov
daa8f7dfc6 Partially back-port #25075 to 4.x 2024-03-05 12:15:39 +03:00
MaximSmolskiy
c346ee1c29 Improve contours approximations in ChessBoardDetector::generateQuads 2024-03-03 23:05:29 +03:00
Adrian Kretz
e0b489e917
Merge pull request #25050 from akretz:fix_issue_24330
Handle degenerate cases in RQDecomp3x3 #25050

The point of the Givens rotations here is to iteratively set the lower left matrix entries to zero. If an element is zero already, we don't need to do anything. This resolves #24330.

### Pull Request Readiness Checklist

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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-02-27 08:10:21 +03:00
Maxim Smolskiy
853f7ff904
Merge pull request #25090 from MaximSmolskiy:compensate-edge-length-in-ChessBoardDetector-generateQuads-attempt-2
Compensate edge length in ChessBoardDetector::generateQuads (attempt 2) #25090

### Pull Request Readiness Checklist

New attempt for #24833, which was reverted as #25036.

Locally I fixed `Calib3d_StereoCalibrate_CPP.regression` test by corners refinement using `cornerSubPix` function

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-02-26 12:12:53 +03:00
Markus Murschitz
f9a7d3b90c changed formular in documentation of reprojectImageTo3D to fit the actual algorithm 2024-02-23 23:09:12 +01:00
Vadim Pisarevsky
2d204243af
Merge pull request #25064 from vpisarev:em_5point_fix
Fix very slow compilation of five-point algorithm on some platforms (e.g. Qualcomm) #25064

Thanks to our big friend and long-term contributor for the patch!

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-02-22 12:04:13 +03:00
Alexander Smorkalov
bd73b7bcf5
Merge pull request #25028 from asmorkalov:as/fisheye_solvepnp
solvePnP implementation for Fisheye camera model #25028

Credits to Linfei Pan
Extracted from https://github.com/opencv/opencv/pull/24052

**Warning:** The patch changes Obj-C generator behaviour and adds "fisheye_" prefix for all ObjC functions from namespace.

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake

Co-authored-by: lpanaf <linpan@student.ethz.ch>
Co-authored-by: Vadim Levin <vadim.levin@xperience.ai>
2024-02-16 17:54:40 +03:00
Alexander Smorkalov
7bea25a60c
Merge pull request #25030 from asmorkalov:as/fisheye_initial_f
Changed initial estimation for F in fisheye calibration
2024-02-16 17:18:43 +03:00
Alexander Smorkalov
78a765cb81 Reverted Compensate edge length in ChessBoardDetector::generateQuads #24833 2024-02-16 12:12:00 +03:00
lpanaf
b87058f7ac Changed initial estimation for F in fisheye calibration. 2024-02-15 16:22:30 +03:00
Alexander Smorkalov
a9f15d7372
Merge pull request #24833 from MaximSmolskiy:compensate-edge-length-in-ChessBoardDetector-generateQuads
Compensate edge length in ChessBoardDetector::generateQuads
2024-02-15 13:22:13 +03:00
Alexander Smorkalov
82914e442c
Merge pull request #24710 from MaximSmolskiy:do-not-dilate-binary-images-on-first-iteration-in-findChessboardCorners
Do not dilate binary images on first iteration in findChessboardCorners
2024-02-12 15:40:02 +03:00
Maksym Ivashechkin
f300deb569
Merge pull request #24987 from ivashmak:bugfix_infinite_loop
bug fix infinite loop #24987

Fixes #24967

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
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Bugfix to #24967
2024-02-12 10:16:19 +03:00
MaximSmolskiy
bcbc74d4cd Do not dilate binary images on first iteration in findChessboardCorners 2024-02-08 01:31:29 +03:00
Maxim Smolskiy
28d22d7b84
Merge pull request #24779 from MaximSmolskiy:fix-bug-in-ChessBoardDetector-findQuadNeighbor
Fix bug in ChessBoardDetector::findQuadNeighbors #24779

### Pull Request Readiness Checklist

`corners` and `neighbors` indices means not filling order, but relative position. So, for example if `quad->count = 2`, it doesn't mean that `quad->neighbors[0]` and `quad->neighbors[1]` are filled. And we should should iterate over all four `neighbors`.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2024-02-06 15:16:12 +03:00
MaximSmolskiy
3640217772 Compensate edge length in ChessBoardDetector::generateQuads 2024-01-08 23:13:31 +03:00
Alexander Smorkalov
03d1760dd5 Added exception warning to calibrateCamera description. 2023-12-26 09:23:11 +03:00
Maxim Smolskiy
4884083019
Merge pull request #24667 from MaximSmolskiy:fix-mismatch-and-simplify-code-in-ChessBoardDetector-findQuadNeighbors
Fix mismatch and simplify code in ChessBoardDetector::findQuadNeighbors #24667

### Pull Request Readiness Checklist

Сode doesn't match comment. 
If we want check `1:4` edges ratio and `edge_len` is squared edge length, then we should check
```
ediff > 15*edge_len
```
with constant `15`, not `32`, because
```
ediff > 15*edge_len2 <=> edge_len1 - edge_len2 > 15*edge_len2 <=> edge_len1 > 16*edge_len2 <=> 1:4 edges ratio
```

But for me it's better and simpler to directly check `edge_len1 > 16*edge_len2`

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-12-24 11:45:20 +03:00
thewoz
e64c5dc4c6
Merge pull request #24546 from thewoz:checkerboard
Check Checkerboard Corners #24546

What I did was get you to pull out of findChessboardCorners cornres the whole part that "checks" and sorts the corners of the checkerboard if present.
The main reason for this is that findChessboardCorners is often very slow to find the corners and this depends in that the size the contrast etc of the checkerboards can be very different from each other and writing a function that works on all kinds of images is complicated. 
So I find it very useful to have the ability to write your own code to process the image and then have a function that controls or orders the corners.


### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-12-20 18:01:39 +03:00
Alexander Smorkalov
465e601e10
Merge pull request #24713 from MaximSmolskiy:improve-icvSmoothHistogram256
Improve icvSmoothHistogram256
2023-12-19 18:39:34 +03:00
Alexander Smorkalov
509c1afb8d
Merge pull request #24659 from MaximSmolskiy:fix-bug-in-ChessBoardDetector-cleanFoundConnectedQuads
Fix bug in ChessBoardDetector::cleanFoundConnectedQuads
2023-12-19 16:05:29 +03:00
MaximSmolskiy
398611b7e8 Improve icvSmoothHistogram256 2023-12-18 16:56:05 +03:00
Vincent Rabaud
915e39cdf0 Empty vectors before filling them in ChessBoardDetector::processQuads
It seems the port in https://github.com/opencv/opencv/pull/11703 lost
the initialization.
2023-12-15 14:48:14 +01:00
Maxim Smolskiy
b1b59c87b9
Merge pull request #24605 from MaximSmolskiy:speed-up-ChessBoardDetector-findQuadNeighbors
Speed up ChessBoardDetector::findQuadNeighbors #24605

### Pull Request Readiness Checklist

Replaced brute-force algorithm with O(N^2) time complexity with kd-tree with something like O(N * log N) time complexity (maybe only in average case).

For example, on image from #23558 without quads filtering (by using `CALIB_CB_FILTER_QUADS` flag) finding chessboards corners took ~770 seconds on my laptop, of which finding quads neighbors took ~620 seconds.

Now finding chessboards corners takes ~155-160 seconds, of which finding quads neighbors takes only ~5-10 seconds.

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
2023-12-11 19:11:58 +03:00
MaximSmolskiy
2f0de10120 Fix bug in ChessBoardDetector::cleanFoundConnectedQuads 2023-12-06 22:46:09 +03:00
Vincent Rabaud
7f0a094e4e Fix stereoRectify image boundaries again.
This should have been fixed in https://github.com/opencv/opencv/pull/24035
2023-12-05 13:36:17 +01:00
Tomoaki Teshima
c7ed293484 typo fix 2023-12-02 13:30:01 +09:00